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wav2vec2-finetune-authentic-only
arkitex/wav2vec2-finetune-authentic-only
wav2vec2-finetune-authentic-only is a automatic speech recognition model from arkitex. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Apr 17, 2025
- Updated
- May 3, 2025
- SHA
- 54e38475
Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
wav2vec2-finetune-authentic-only
This model is a fine-tuned version of facebook/wav2vec2-base on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4832
- Wer: 0.3169
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.2515 | 0.1337 | 500 | 2.9469 | 1.0 |
| 1.4619 | 0.2674 | 1000 | 0.9826 | 0.5937 |
| 0.7206 | 0.4011 | 1500 | 0.8086 | 0.4917 |
| 0.6012 | 0.5348 | 2000 | 0.7485 | 0.4530 |
| 0.5422 | 0.6684 | 2500 | 0.7128 | 0.4329 |
| 0.5063 | 0.8021 | 3000 | 0.6346 | 0.4055 |
| 0.479 | 0.9358 | 3500 | 0.6450 | 0.4001 |
| 0.44 | 1.0695 | 4000 | 0.6126 | 0.3856 |
| 0.4103 | 1.2032 | 4500 | 0.5970 | 0.3747 |
| 0.396 | 1.3369 | 5000 | 0.5792 | 0.3780 |
| 0.3822 | 1.4706 | 5500 | 0.5786 | 0.3643 |
| 0.3706 | 1.6043 | 6000 | 0.5387 | 0.3507 |
| 0.3669 | 1.7380 | 6500 | 0.5292 | 0.3546 |
| 0.3544 | 1.8717 | 7000 | 0.5145 | 0.3436 |
| 0.3492 | 2.0053 | 7500 | 0.5322 | 0.3342 |
| 0.3066 | 2.1390 | 8000 | 0.5284 | 0.3323 |
| 0.3006 | 2.2727 | 8500 | 0.5248 | 0.3333 |
| 0.2954 | 2.4064 | 9000 | 0.4983 | 0.3221 |
| 0.2914 | 2.5401 | 9500 | 0.4844 | 0.3202 |
| 0.2841 | 2.6738 | 10000 | 0.4881 | 0.3167 |
| 0.2816 | 2.8075 | 10500 | 0.4815 | 0.3167 |
| 0.2777 | 2.9412 | 11000 | 0.4832 | 0.3169 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0
- Datasets 3.5.0
- Tokenizers 0.21.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Apr 17, 2025
- Updated
- May 3, 2025